Most of the researchers and scientists are striving towards the enhancement of Genetic Algorithm (GA) which is under the field of Bio-Informatics. In general a Genetic Algorithm is solved by using Crossover and Mutation method. Here Crossover refers to a random shifting of a child in order to make new tours and Mutation adjust the Crossover. However, a Genetic Algorithm is efficient in itself, yet there are two problems that can be further optimized to get better results. Those problems are: During the encoding of tour if population is less, it may result in identical solutions, which is invalid. To solve the first problem we need to increase the population size. But on doing so, the time complexity will rise exponentially. In this paper I am proposing a modified Genetic Algorithm which essentially aims at eliminating the above stated problems. Furthermore, I will try to demonstrate this solution by an application that might be used by a detection based database. © Research India Publications.